CaseStudy1

Breweries <- read_csv("Breweries.csv")
library(ggmap)
library(ggplot2)
library(ggmap)
library(maps)
library(mapdata)
library(openintro)
library(plotly)

Data

states <- read.csv("states.csv")
dat = Breweries

#obtain the count of the number of breweres by state
state_count = dat %>% group_by(State) %>% count() %>% arrange(-n)

#states <- map_data("state")

#states  = states %>% mutate(State_ABB = state2abbr(region))

#states = states %>% inner_join(state_count, by = c("State_ABB" = "State"))

Bar Chart

library(billboarder)
billboarder() %>%
  bb_barchart(state_count)

Heatmap

#Here we are creating heatmap to show quanties. 
heat_map = ggplot(data = states) + 
  geom_polygon(aes(x = long, y = lat, fill = n, group = group), color = "white") + 
  coord_fixed(1.3) +
  scale_fill_gradientn(colours = rev(heat.colors(10)),na.value = "grey90",
                       guide = guide_colourbar(barwidth = 5, barheight = 0.4,
                                               #put legend title on top of legend
                                               title.position = "top")) + 
  labs(title = "Quantities of Breweries by State")
  
ggplotly(heat_map)